Construction Of A FR-Petri Net Model And Its Application In Manufacturing System Performance Evaluation

With the continuous development of the economy and the improvement of people's living standards,customer demands for product features are becoming more and more personalized and diversified.The complex external environment exacerbates the contradictions of traditional manufacturing systems such as high cost,long cycle and low equipment utilization.An increasing number of enterprises are urgently adopting information technologies such as the Industrial Internet of Things and artificial intelligence to improve their production management capabilities.Therefore,it is of great significance to accurately analyze the working process of the manufacturing system,and to evaluate and quantify the effect of new technologies and methods in improving the productivity of the manufacturing system.Petri net has been a powerful process modelling tool for nearly six decades and is widely used in the performance evaluation of complex systems.For the complexity and uncertainty of the production process of modern enterprises,stochastic Petri net and fuzzy Petri net have been paid more attention by scholars.However,the uncertainty in the manufacturing system not only exists in the change of individual device or state in actual production activities,but also in the complex relation between the interconnection of equipment factors or state variables.Based on the point,the study proposes a Fuzzy Relation Petri Net(FR-Petri Net)model and applies it to the performance evaluation of complex manufacturing systems.The main research is as follows:(1)This study adopts fuzzy set to represent the uncertainty relation between equipment operation time and failure rate in manufacturing systems,proposes and defines the FR-Petri net model to describe the manufacturing system problem.A fuzzy mathematical planning method based on FR-Petri net with machine utilization as the objective is established.At the same time,the results of the study are compared and analysed with those obtained from existing model,i.e.Stochastic Petri net with fuzzy parameters.(2)Stateflow and Petri net have similar operating mechanisms when describing the operation process of the manufacturing system.Therefore,a dynamic simulation of the manufacturing system process based on the FR-Petri net model using the Stateflow tool illustrates the reliability of the model through simulation results.(3)Applying the FR-Petri net model and simulation method to the performance evaluation of a typical class of process manufacturing systems.The simulation of the manufacturing system considers two scenarios: Independent loading and unloading of parts and random arrival of parts.Based on the results,not only the influence of the different parameters in the fuzzy relation on the performance is analysed,but also the performance of the manufacturing system is evaluated in both cases.The results show that a manufacturing system with independent loading and unloading of parts has better performance than a single robot with shared loading and unloading of parts.When parts arrive randomly,the system performance is not only affected by the random arrival time,but also by the number of arrivals.The features and innovations of this research include: 1)In response to the inadequacy of existing stochastic Petri net and fuzzy Petri net which mainly study the uncertainty of single or multiple factors,the study considers the uncertainty of the inter-constrained relationship between factors,such as the uncertainty between equipment operation and failure in manufacturing systems;2)Taking the uncertainty relation between equipment operation time and failure frequency in manufacturing systems as an example,a novel FRPetri net model is proposed using a linear fuzzy function to describe it,and the corresponding fuzzy mathematical planning method and system simulation process are established.This research,selected from the National Natural Science Foundation of China,proposes a novel FR-Petri net model,which to a certain extent enriches and extends the theoretical study of Petri nets.The model and some of the results can be applied to the modelling of complex manufacturing systems and the quantitative analysis of manufacturing system performance improvements for the Internet of Things,artificial intelligence,etc.,helping manufacturing companies to accurately assess the production benefits.